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Published on: May 17, 2019
[Contribution and challenges of Big Data in oncology]
Pierre Saintigny1, Jean-Philippe Foy2, Anthony Ferrari3
1Université Lyon, université Claude-Bernard Lyon 1, centre Léon-Bérard, centre de recherche en cancérologie de Lyon, CNRS 5286, Inserm 1052, 69008 Lyon, France; Centre Léon-Bérard, département de médecine et département de recherche translationnelle et de l'innovation, 28, rue Laënnec, 28, rue Laennec, 69373 Lyon cedex 08, France.
Abstract:
Since the first draft of the human genome sequence published in 2001, the cost of sequencing has dramatically decreased. The development of new technologies such as next generation sequencing led to a comprehensive characterization of a large number of tumors of various types as well as to significant advances in precision medicine. Despite the valuable information this technological revolution has allowed to produce, the vast amount of data generated resulted in the emergence of new challenges for the biomedical community, such as data storage, processing and mining. Here, we describe the contribution and challenges of Big Data in oncology.
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